Search Results for "raspberry-gpio-python" - Page 13
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351 programs for "raspberry-gpio-python" with 2 filters applied:
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pRobot is something like Pokémon for computer scientists. Each player creates a computer program, a so-called pRobot. Then all the pRobots are thrown into a virtual arena, the war-ground. Within that arena they can walk, reproduce, and fight.
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Copter! is a SimCopter clone written in C++. Copter! will feature much more than the original SimCopter, and will be very moddable through it's modular design. Mods will be released which allow the player to be a policeman, or other characters.
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PyOP (Python Optimus Prime bot) is an Open Source IRC bot written in Python. It's intended to be simple, fast and modular. Support for jabber/MSN is planned.
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aVolve is an evolutionary/genetic algorithm designed to evolve single-cell organisms in a micro ecosystem. It currently uses the JGAP Genetic algorithm, but does include a primitive genetic algorithm written in Python.
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Generic engine to filter information. We wish to show that the power of expression of a filter makes it possible to appreciably reduce the size of the code necessary to extract information and that it is possible in Python.
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Dia-1.6B
Dia-1.6B generates lifelike English dialogue and vocal expressions
... on enterprise GPUs, though CPU and quantized versions are planned. The format supports [S1]/[S2] tags to differentiate speakers and integrates easily into Python workflows. While not tuned to a specific voice, user-provided audio can guide output style. Licensed under Apache 2.0, Dia is intended for research and educational use, with explicit restrictions on misuse like identity mimicry or deceptive content. -
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grok-1
Grok-1 is a 314B-parameter open-weight language model by xAI
Grok-1 is a large-scale language model released by xAI, featuring 314 billion parameters and made available under the Apache 2.0 license. It is designed for text generation and was trained for advanced language understanding and reasoning capabilities. Grok-1 is currently distributed as open weights, with inference support requiring multi-GPU hardware due to its size. The model can be downloaded from Hugging Face and run using the accompanying Python code in the official GitHub repository... -
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mozg is a flexible, fast neurolibrary. It allows one to create, learn and use multi-layer perceptron (MLP), which is the most popular artificial neural network (ANN). This work is based on library originally written by Alexy Filin.
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Representation method of abstract information based on hierarchical network of simplest nodes. Each node can represent both value and attribute. Network is able to accumulate, classify and learn information.
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Cellicone is a project to develop an artificial life organism with the necessary components to make it comparable to biological life as we know it. This includes components ranging from proteins to cells to organs to limbs, and many steps between.
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ERNIE-4.5-300B-A47B-FP8-Paddle
ERNIE 4.5 MoE model in FP8 for efficient high-performance inference
.... It is especially well-suited for production environments requiring high throughput and lower memory use, while maintaining high reasoning and generation quality. The model can be used with FastDeploy and integrates cleanly with Python APIs for prompt-based generation workflows. It supports long context lengths (up to 131,072 tokens) and includes both Chinese and English prompt templates for web search applications. -
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starcoder
Code generation model trained on 80+ languages with FIM support
StarCoder is a 15.5B parameter language model developed by BigCode for code generation tasks across more than 80 programming languages. It is trained on 1 trillion tokens from the permissively licensed dataset The Stack v1.2, using the Fill-in-the-Middle (FIM) objective and Multi-Query Attention to enhance performance. With an extended context window of 8192 tokens and pretraining in bfloat16, StarCoder can generate, complete, or refactor code in various languages, with English as the... -
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DeepSWE-Preview
State-of-the-art RL-trained coding agent for complex SWE tasks
DeepSWE-Preview is a 32.8B parameter open-source coding agent trained solely with reinforcement learning (RL) to perform complex software engineering (SWE) tasks. Built on top of Qwen3-32B, it achieves 59% accuracy on the SWE-Bench-Verified benchmark—currently the highest among open-weight models. The model navigates and edits large codebases using tools like a file editor, bash execution, and search, within the R2E-Gym environment. Its training emphasizes sparse reward signals, test-time... -
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mms-300m-1130-forced-aligner
CTC-based forced aligner for audio-text in 158 languages
... to the TorchAudio forced alignment API. Users can integrate it easily through the Python package ctc-forced-aligner, and it supports GPU acceleration via PyTorch. The alignment pipeline includes audio processing, emission generation, tokenization, and span detection, making it suitable for speech analysis, transcription syncing, and dataset creation. This model is especially useful for researchers and developers working with low-resource languages or building multilingual speech systems. -
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yolo-world-mirror
Mirror of Ultralytics YOLO-World model weights for object detection
... descriptions. These weights are compatible with Ultralytics’ tooling and documentation, making it easier for developers to deploy or fine-tune the model. The mirror allows users to work with YOLO-World models through a centralized platform without downloading from alternate sources. It enables flexible integration with Ultralytics’ Python API or CLI tools for real-time and high-performance object detection tasks. -
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segmentation-3.0
Speaker segmentation model for 10s audio chunks with powerset labels
segmentation-3.0 is a voice activity and speaker segmentation model from the pyannote.audio framework, designed to analyze 10-second mono audio sampled at 16kHz. It outputs a (num_frames, num_classes) matrix using a powerset encoding that includes non-speech, individual speakers, and overlapping speech for up to three speakers. Trained with pyannote.audio 3.0.0 on a rich blend of datasets—including AISHELL, DIHARD, VoxConverse, and more—it enables downstream tasks like voice activity... -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
MiniMax-M1 is the world’s first open-weight, large-scale hybrid-attention reasoning model designed for long-context and complex reasoning tasks. Powered by a hybrid Mixture-of-Experts (MoE) architecture combined with a lightning attention mechanism, it efficiently supports context lengths up to 1 million tokens—eight times larger than many contemporary models. MiniMax-M1 significantly reduces computational overhead at generation time, consuming only about 25% FLOPs compared to comparable... -
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ERNIE-4.5-0.3B-Base-PT
Compact 360M text model with high efficiency and fine-tuning support
... with support for SFT, LoRA, and DPO training methods, making it highly adaptable. Compatible with the Hugging Face Transformers library, the model can be easily used in Python for inference or deployed via FastDeploy. This variant emphasizes portability and accessibility, enabling fast deployment even on less powerful hardware. Ideal for developers seeking a smaller model for prototyping, educational use, or lightweight production tasks. -
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Nanonets-OCR-s
State-of-the-art image-to-markdown OCR model
Nanonets-OCR-s is an advanced image-to-markdown OCR model that transforms documents into structured and semantically rich markdown. It goes beyond basic text extraction by intelligently recognizing content types and applying meaningful tags, making the output ideal for Large Language Models (LLMs) and automated workflows. The model expertly converts mathematical equations into LaTeX syntax, distinguishing between inline and display modes for accuracy. It also generates descriptive <img> tags... -
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FLUX.1-dev
Powerful 12B parameter model for top-tier text-to-image creation
FLUX.1-dev is a powerful 12-billion parameter rectified flow transformer designed for generating high-quality images from text prompts. It delivers cutting-edge output quality, just slightly below the flagship FLUX.1 [pro] model, and matches or exceeds many closed-source competitors in prompt adherence. The model is trained using guidance distillation, making it more efficient and accessible for developers and artists alike. FLUX.1-dev is openly available with weights provided to support... -
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stable-diffusion-v1-4
Text-to-image diffusion model for high-quality image generation
stable-diffusion-v1-4 is a high-performance text-to-image latent diffusion model developed by CompVis. It generates photo-realistic images from natural language prompts using a pretrained CLIP ViT-L/14 text encoder and a UNet-based denoising architecture. This version builds on v1-2, fine-tuned over 225,000 steps at 512×512 resolution on the “laion-aesthetics v2 5+” dataset, with 10% text-conditioning dropout for improved classifier-free guidance. It is optimized for use with Hugging Face’s...
